Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures
Produktnummer:
18f8eed2f7a2674c74b813cbae1cb66e13
| Themengebiete: | artificial intelligence image processing image reconstruction image segmentation imaging systems medical images medical imaging neural networks |
|---|---|
| Veröffentlichungsdatum: | 11.10.2019 |
| EAN: | 9783030326883 |
| Sprache: | Englisch |
| Seitenzahl: | 192 |
| Produktart: | Kartoniert / Broschiert |
| Herausgeber: | Arbel, Tal Baumgartner, Christian Dalca, Adrian Drechsler, Klaus Erdt, Marius González Ballester, Miguel Ángel Greenspan, Hayit Linguraru, Marius George Oyarzun Laura, Cristina Shekhar, Raj Sudre, Carole H. Tanno, Ryutaro Wells, William M. Wesarg, Stefan |
| Verlag: | Springer International Publishing |
| Untertitel: | First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings |
Produktinformationen "Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures"
This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
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